Responsible AI

IBM is helping to advance responsible AI with a multidisciplinary, multidimensional approach

Learn about integrated AI governance at IBM Read our POV on responsible synthetic data
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Mastering AI governance: How to leverage technology to simplify compliance.

Discover how to embed AI governance and streamline compliance in IBM’s expert-led webinar.

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Now is the moment for responsible AI

Businesses are facing an increasingly complex, ever-changing global regulatory landscape when it comes to AI. The IBM approach to responsible AI balances innovation with responsibility, helping you adopt trusted AI at scale.

Latest updates

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Four strategic shifts to accelerate value with AI governance

AI governance isn't just about compliance — it's a strategic lever for innovation, scale and value.
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Transforming change management with responsible AI

Prioritizing trust, transparency, skills and agility can help organizations lead the way through AI transformation.

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Responsibly scaling AI agents across the enterprise

Understanding the unique opportunities, risks and mitigations of AI agents is a critical first step toward scaling them responsibly.
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Accelerating innovation through centralized AI governance

The IBM Office of Privacy and Responsible Technology is scaling responsible AI and unlocking business value through integrated AI governance.
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What are the costs of not implementing AI governance?

Just as important as what AI governance helps organizations achieve is what it helps organizations avoid. Find out the extensive potential costs of not implementing an AI governance program.
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Five ways responsible AI has changed in the last 5 years

Through the last five years of AI evolution, the IBM Responsible Technology Board has helped IBM responsibly innovate by guiding the development and implementation of ethical guidelines for AI.
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Celebrating the 5th anniversary of the IBM Responsible Technology Board

Members of the IBM Responsible Technology Board reflect on their experiences helping to ensure that AI is used responsibly and for the benefit of all of society.
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5 best practices for responsible synthetic data

Get your organization ready to capitalize on the benefits of synthetic data for AI.
Our principles and pillars The Principles for Trust and Transparency are the guiding values that distinguish the IBM approach to responsible AI.
Read the Principles for Trust and Transparency
The purpose of AI is to augment human intelligence

IBM believes AI should make all of us better at our jobs, and that the benefits of the AI era should touch the many, not just the elite few.

 Data and insights belong to their creator

IBM clients’ data is their data, and their insights are their insights. We believe that government data policies should be fair and equitable and prioritize openness.

 Technology must be transparent and explainable

Companies must be clear about who trains their AI systems, what data was used in training and, most importantly, what went into the recommendations of their algorithms.
The Principles are supported by the Pillars of Trust, our foundational properties for responsible AI.
Explainability

Good design does not sacrifice transparency in creating a seamless experience.
Fairness

Properly calibrated, AI can assist humans in making choices more fairly.
Robustness

As systems are employed to make crucial decisions, AI must be secure and robust.
Transparency

Transparency reinforces trust, and the best way to promote transparency is through disclosure.
Privacy

AI systems must prioritize and safeguard consumers’ privacy and data rights.
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Foundation models: Opportunities, risks and mitigations Read the paper
Putting principles into action

The IBM Responsible Technology Board’s mission is to provide governance, standards and practical application of principles for how IBM develops and deploys AI and emerging technologies like quantum computing.

It enables IBM teams to act with confidence, speed, and measurable impact in accordance with the company’s values—to advance technology responsibly for our clients, partners and the world.

Learn more about the history of the Board and read its latest POVs and perpectives.

 
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    Accelerate responsible, transparent and explainable data and AI workflows.

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    Partnerships and collaborations

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    Helping researchers and developers make better AI design decisions

    IBM and the University of Notre Dame have published BenchmarkCards, a collection of datasets, benchmarks and mitigations that helps guides the development of safe and transparent AI systems.
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    Exploring the future of responsible AI in finance

    At the Notre Dame-IBM Tech Ethics Lab, industry leaders gathered to discuss the opportunities and challenges of responsible AI in finance.
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    Fostering greater transparency across the data ecosystem

    Co-created by IBM, the Data & Trust Alliance's new Data Provenance Standards offer a first-of-their-kind metadata taxonomy to support transparency about data provenance.
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    Proactively generating value with responsible AI

    Experts from IBM and University of Notre Dame outline recommendations for getting the best ROI from responsible AI investments.
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    Partnership on AI shares risk mitigation strategies for the open foundation model value chain

    With input from IBM, Partnership on AI's new report explores safeguards for open foundation models.
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    The Data & Trust Alliance offers new policy roadmap for AI governance

    Co-authored by IBM, the Data & Trust Alliance's new policy roadmap provides recommendations for balancing AI innovation with AI safety.

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    Pulitzer Center launches program to train 1,000 journalists on AI reporting

    With support from the Notre Dame-IBM Technology Ethics Lab, the Pulitzer Center launches the AI Spotlight Series, a global training initiative.
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    IBM and Meta launch the AI Alliance

    IBM and Meta launch the AI Alliance in collaboration with over 50 founding members and collaborators globally.
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    AI Governance Alliance releases Briefing Paper Series

    In collaboration with IBM, the World Economic Forum offers three briefing papers to help guide responsible transformation with AI.

    Next steps

    Find out how IBM can help you accelerate your responsible AI journey.

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